431 research outputs found
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Extension of 4-8 Texture Hierarchies to Large Video Processing and Visualization
The purpose of this Techbase was to reduce to practice the tiled 4-8 texture hierarchy for the display of video imagery (i.e. sequences of frames). The immediate intent was to demonstrate its use in the analysis and display of sensor imagery. As sensors are increasing in resolution the physical amount of imagery that needs to be displayed can quickly overwhelm most display systems. For example, a sensor with a horizontal resolution of over 8000 pixels would generate an image over 10 feet wide on a standard 72 DPI display. Breaking an image into tiles, and then decomposing each tile into a multiresolution hierarchy, allows a user (or software) to efficiently select and display only those parts of the image that are of interest to the user. The originator of the idea of 4-8 Texture Hierarchies was Dr. Mark Duchaineau, and we consulted with him in much of our work. We also consulted with Dan Knight, from SequoiaTek Corp., who is a contractor responsible for implementing the viewers for our applications. Most of the code for actual 4-8 Texture Hierarchy generation already existed; a large focus of the Techbase was to determine how to best use what was available for video imagery. The majority of progress was made in specifying and implementing the software framework, which turned out to be rather involved. This framework is to support the creation, storage, and display of images, both tiled and untiled. A first albeit incomplete version was successfully tested in the field in August 2007. The framework structures the process of collecting and processing images conceptually as a pipeline, where work is passed along and a different operation is performed at each stage. In practice, the pipeline is implemented by a group of processes (not threads), or 'workers', each responsible for a specific type of operation. Associated with these workers is a pool of memory (cache). As each process finishes its work, it places the results into the cache and sends a message to the process responsible for the next operation, including in the message an identifier allowing the recipient to locate the data to be worked on. Conceptually this is akin to transferring mail from person to person by placing it into and removing it from a group of mail slots, rather than handing it to the next person directly. So for example, to capture, tile, and store imagery to disk, one worker would be responsible for obtaining an image from an electro-optical sensor. Another would be responsible for breaking the image into tiles, and another for performing a decorrelating transform for entropy reduction and multiresolution representation. Still another would be responsible for compression, and another for storage. To maximize robustness in an experimental environment, we created a manager that could monitor, kill, restart, and configure the entire processing pipeline, including the shared cache and worker processes. In the event of hardware or software failure, individual elements of the pipeline were restored automatically and with minimum data loss. Working with Mark Duchaineau we attempted to determine a set of ideal coefficients for the wavelet used to create the multiresolution hierarchy. While a workable set exists, it produces undesirable artifacts at high levels of loss, so more work needs to be done to identify a more ideal set. The tiler and data structures for tiling and display have been added to the code base we developed. As currently implemented it takes approximately one second to tile and build a multiresolution hierarchy for an 11-megapixel image on a 3.8 GHz Pentium 4. This is too slow for some uses, so some work will probably need to be done to optimize the code. We may be able to leverage commodity graphics processors to gain extra speed. With the advent of quad-core CPUs it may also be possible to get required throughput by tiling the image and then having several processes run in parallel to build the multiresolution hierarchies for the resulting tiles. Additionally, more work needs to be done to define a data format for storing image tiles on disk, as well as retrieving and displaying them. As this functionality is desirable (and required, if we are to make large data easily viewable) we will be spending a lot of time developing this. As a final note, it was recently brought to our attention that Oracle provides an extension to its database technology that provides most, if not all, of the functionality that we are working on as part of this project. We will be investigating this further; if a suitable solution already exists it may be more valuable time-wise to integrate it into projects that require storing and displaying large images
X-ray physico-chemical imaging during activation of cobalt-based Fischer-Tropsch synthesis catalysts
The imaging of catalysts and other functional materials under reaction conditions has advanced significantly in recent years. The combination of the computed tomography (CT) approach with methods such as X-ray diffraction (XRD), X-ray fluorescence (XRF) and X-ray absorption near-edge spectroscopy (XANES) now enables local chemical and physical state information to be extracted from within the interiors of intact materials which are, by accident or design, inhomogeneous. In this work, we follow the phase evolution during the initial reduction step(s) to form Co metal, for Co-containing particles employed as Fischer–Tropsch synthesis (FTS) catalysts; firstly, working at small length scales (approx. micrometre spatial resolution), a combination of sample size and density allows for transmission of comparatively low energy signals enabling the recording of ‘multimodal’ tomography, i.e. simultaneous XRF–CT, XANES–CT and XRD–CT. Subsequently, we show high-energy XRD–CT can be employed to reveal extent of reduction and uniformity of crystallite size on millimetre-sized TiO2 trilobes. In both studies, the CoO phase is seen to persist or else evolve under particular operating conditions and we speculate as to why this is observed
Understanding the unsteady pressure field inside combustion chambers of compression-ignited engines using a computational fluid dynamics approach
[EN] In this article, a numerical methodology for assessing combustion noise in compression ignition engines is described with the specific purpose of analysing the unsteady pressure field inside the combustion chamber. The numerical results show consistent agreement with experimental measurements in both the time and frequency domains. Nonetheless, an exhaustive analysis of the calculation convergence is needed to guarantee an independent solution. These results contribute to the understanding of in-cylinder unsteady processes, especially of those related to combustion chamber resonances, and their effects on the radiated noise levels. The method was applied to different combustion system configurations by modifying the spray angle of the injector, evidencing that controlling the ignition location through this design parameter, it is possible to decrease the combustion noise by minimizing the resonance contribution. Important efficiency losses were, however, observed due to the injector/bowl matching worsening which compromises the performance and emissions levels.The authors want to express their gratitude to CONVERGENT SCIENCE Inc. and Convergent Science GmbH for their kind support for performing
the CFD calculations using CONVERGE software.Torregrosa, AJ.; Broatch, A.; Margot, X.; Gómez-Soriano, J. (2018). Understanding the unsteady pressure field inside combustion chambers of compression-ignited engines using a computational fluid dynamics approach. International Journal of Engine Research. 1-13. https://doi.org/10.1177/1468087418803030S113Benajes, J., Novella, R., De Lima, D., & Tribotté, P. (2014). Analysis of combustion concepts in a newly designed two-stroke high-speed direct injection compression ignition engine. International Journal of Engine Research, 16(1), 52-67. doi:10.1177/1468087414562867Costa, M., Bianchi, G. M., Forte, C., & Cazzoli, G. (2014). A Numerical Methodology for the Multi-objective Optimization of the DI Diesel Engine Combustion. Energy Procedia, 45, 711-720. doi:10.1016/j.egypro.2014.01.076Navid, A., Khalilarya, S., & Taghavifar, H. (2016). 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International Journal of Engine Research, 5(1), 83-91. doi:10.1243/146808704772914264Broatch, A., Margot, X., Gil, A., & Christian Donayre, (José). (2007). Computational study of the sensitivity to ignition characteristics of the resonance in DI diesel engine combustion chambers. Engineering Computations, 24(1), 77-96. doi:10.1108/02644400710718583Eriksson, L. J. (1980). Higher order mode effects in circular ducts and expansion chambers. The Journal of the Acoustical Society of America, 68(2), 545-550. doi:10.1121/1.384768Broatch, A., Margot, X., Novella, R., & Gomez-Soriano, J. (2017). Impact of the injector design on the combustion noise of gasoline partially premixed combustion in a 2-stroke engine. Applied Thermal Engineering, 119, 530-540. doi:10.1016/j.applthermaleng.2017.03.081Tutak, W., & Jamrozik, A. (2016). Validation and optimization of the thermal cycle for a diesel engine by computational fluid dynamics modeling. Applied Mathematical Modelling, 40(13-14), 6293-6309. doi:10.1016/j.apm.2016.02.021Payri, F., Benajes, J., Margot, X., & Gil, A. (2004). CFD modeling of the in-cylinder flow in direct-injection Diesel engines. Computers & Fluids, 33(8), 995-1021. doi:10.1016/j.compfluid.2003.09.003Benajes, J., Novella, R., De Lima, D., & Thein, K. (2017). Impact of injection settings operating with the gasoline Partially Premixed Combustion concept in a 2-stroke HSDI compression ignition engine. Applied Energy, 193, 515-530. doi:10.1016/j.apenergy.2017.02.044Lesieur, M., Métais, O., & Comte, P. (2005). Large-Eddy Simulations of Turbulence. doi:10.1017/cbo9780511755507Pope, S. B. (2004). Ten questions concerning the large-eddy simulation of turbulent flows. New Journal of Physics, 6, 35-35. doi:10.1088/1367-2630/6/1/035Silva, C. F., Leyko, M., Nicoud, F., & Moreau, S. (2013). Assessment of combustion noise in a premixed swirled combustor via Large-Eddy Simulation. 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Assessment of flamelet versus multi-zone combustion modeling approaches for stratified-charge compression ignition engines. International Journal of Engine Research, 17(3), 280-290. doi:10.1177/1468087415571006Torregrosa, A. J., Broatch, A., Gil, A., & Gomez-Soriano, J. (2018). Numerical approach for assessing combustion noise in compression-ignited Diesel engines. Applied Acoustics, 135, 91-100. doi:10.1016/j.apacoust.2018.02.006Torregrosa, A., Olmeda, P., Degraeuwe, B., & Reyes, M. (2006). A concise wall temperature model for DI Diesel engines. Applied Thermal Engineering, 26(11-12), 1320-1327. doi:10.1016/j.applthermaleng.2005.10.021Broatch, A., Javier Lopez, J., García-Tíscar, J., & Gomez-Soriano, J. (2018). Experimental Analysis of Cyclical Dispersion in Compression-Ignited Versus Spark-Ignited Engines and Its Significance for Combustion Noise Numerical Modeling. Journal of Engineering for Gas Turbines and Power, 140(10). doi:10.1115/1.4040287Molina, S., García, A., Pastor, J. 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Optimizing Blocker Usage On NIF Using Image Analysis And Machine Learning*
A new multistage lattice vector quantization with adaptive subband thresholding for image compression
Lattice vector quantization (LVQ) reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ) using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images
Interaction of Imidazole Containing Hydroxamic Acids with Fe(III): Hydroxamate Versus Imidazole Coordination of the Ligands
Solution equilibrium studies on Fe(III) complexes formed with imidazole-4-carbohydroxamic acid (Im-4-Cha),
N-Me-imidazole-4-carbohydroxamic acid (N-Me-Im-4-Cha), imidazole-4-acetohydroxamic acid (Im-4-Aha), and histidinehydroxamic acid (Hisha) have been performed by using pH-potentiometry, UV-visible spectrophotometry, EPR, ESI-MS, and H1-NMR methods. All of the obtained results demonstrate that the imidazole moiety is able to play an important role very often in the interaction with Fe(III), even if this metal ion prefers the hydroxamate chelates very much. If the imidazole moiety is in
α-position to the hydroxamic one (Im-4-Cha and N-Me-Im-4-Cha) its coordination to the metal ion is indicated unambiguously by our results. Interestingly, parallel formation of (Nimidazole, Ohydroxamate), and (Ohydroxamate, Ohydroxamate) type chelates seems probable with N-Me-Im-4-Cha. The imidazole is in β-position to the hydroxamic moiety in Im-4-Aha and an intermolecular noncovalent (mainly H-bonding) interaction seems to organize the intermediate-protonated molecules in this system. Following the formation of mono- and bishydroxamato mononuclear complexes, only EPR silent species exists in the Fe(III)-Hisha system above pH 4, what suggests the rather significant “assembler activity” of the imidazole (perhaps together with the ammonium moiety)
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
5D operando tomographic diffraction imaging of a catalyst bed
We report the results from the first 5D tomographic diffraction imaging experiment of a complex Ni-Pd/CeO2-ZrO2/Al2O3 catalyst used for methane reforming. This five-dimensional (three spatial, one scattering and one dimension to denote time/imposed state) approach enabled us to track the chemical evolution of many particles across the catalyst bed and relate these changes to the gas environment that the particles experience. Rietveld analysis of some 2 × 106 diffraction patterns allowed us to extract heterogeneities in the catalyst from the Å to the nm and to the μm scale (3D maps corresponding to unit cell lattice parameters, crystallite sizes and phase distribution maps respectively) under different chemical environments. We are able to capture the evolution of the Ni-containing species and gain a more complete insight into the multiple roles of the CeO2-ZrO2 promoters and the reasons behind the partial deactivation of the catalyst during partial oxidation of methane
Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas
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Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
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